Reduced signal on [(11)C]] flumazenil (FMZ) positron emission tomography (PET) is associated with epileptogenic foci. Linear correlations within individuals between parametric and nonparametric images of FMZ binding h...
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Reduced signal on [(11)C]] flumazenil (FMZ) positron emission tomography (PET) is associated with epileptogenic foci. Linear correlations within individuals between parametric and nonparametric images of FMZ binding have been shown, and various methods have been used, without comparison of diagnostic usefulness. Using hippocampal sclerosis (HS) as a test case, we formally compare the diagnostic yield of parametric images obtained either with a parent tracer arterial plasma input function and spectral analysis (yielding volume-of-distribution (VD) images), or with an image-based input function and the simplified reference tissue model (binding potential images, BP-SRTM) with the diagnostic yield of semiquantitative-integrated (ADD) images from 10 to 20 or 20 to 40 mins (ADD1020 and ADD2040). Dynamic 90-min [(11)C] FMZ PET datasets and arterial plasma input functions were available for 15 patients with medically refractory medial temporal lobe epilepsy (TLE) and histologically verified unilateral HS and for 13 control subjects. SPM2 was used for analysis. ADD1020 and ADD2040 images showed decreased FMZ uptake ipsilateral to the epileptogenic hippocampus in 13/15 cases;6/13 had bilateral decreases in the ADD1020 analysis and 5/13 in the ADD2040 analysis. BP-SRTM images detected ipsilateral decreases in 12/15 cases, with bilateral decreases in three. In contrast, VD images showed ipsilateral hippocampal decreases in all 15 patients, with bilateral decreases in three patients. Bilateral decreases in the ADD images tended to be more symmetrical and in one case were more marked contralaterally. Full quantification with an image-independent input should ideally be used in the evaluation of FMZ PET;at least in TLE, intrasubject correlations do not predict equivalent clinical usefulness.
Purpose: To compare the performance of three physiologically-based pharmacokinetic (PBPK) models for predicting gadolinium. contrast agent concentration-time curves (Gd-CTCs) obtained in superior sagittal sinus (SSS),...
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Purpose: To compare the performance of three physiologically-based pharmacokinetic (PBPK) models for predicting gadolinium. contrast agent concentration-time curves (Gd-CTCs) obtained in superior sagittal sinus (SSS), cerebral cortex, and psoas muscle. Materials and Methods: Three published whole-body PBPK models were modified to predict Gd-CTCs in normal-appearing tissue. The models differed in the number of organs modeled and total number of compartments, and were designated as the "well-mixed," "delay," and "dispersion" models. The suitability of the three models to predict Gd-CTC was studied using data from dynamic contrast-enhanced MR perfusion imaging obtained at 1.5T from 10 patients with glioblastoma multiforme and at 3.0T from five patients with liver metastases. Results: The dispersion model produced better fits than the delay model in the SSS (P < 0.0001) and cerebral cortex (P < 0.0001), and better fits than the well-mixed model in psoas muscle (P < 0.005). No model produced better fits than the dispersion model at any of the three locations. Conclusion: In this evaluation, the dispersion model was most robust for prediction of Gd-CTCs derived from dynamic contrast-enhanced (DCE)-MRI. This represents a preliminary step in the development of a PBPK model useful for predicting Gd-CTCs at a time resolution appropriate for dynamic MRI applications.
To solve one-dimensional linear weakly singular integral equations on bounded intervals, with input functions which may be smooth or not, we propose to introduce first a simple smoothing change of variable, and then t...
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To solve one-dimensional linear weakly singular integral equations on bounded intervals, with input functions which may be smooth or not, we propose to introduce first a simple smoothing change of variable, and then to apply classical numerical methods such as product-integration and collocation based on global polynomial approximations. The advantage of this approach is that the order of the methods can be arbitrarily high and that the associated linear systems one has to solve are very well-conditioned.
Interactive computing, including real-time systems and process control, accounts for at least 50% of all computing. Most interactive systems have been programmed in regular batch programming languages. Provisions fo...
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Interactive computing, including real-time systems and process control, accounts for at least 50% of all computing. Most interactive systems have been programmed in regular batch programming languages. Provisions for handling input and output on an advanced level are lacking. A model is presented, called the input-output tool (IOT). It provides the programmer with facilities to hierarchically construct high-level input-driven tools. The elements of the IOT are the input rule, output rule, internal tool definitions, and a tool body consisting of executable statements. Advantages over traditional interactive programming include: 1. It offers a powerful input specification language. 2. It fosters structured programming. 3. Programmers only have to specify their inputs. 4. It allows interleaving and parallelism in entering inputs. 5. The parser handles input type checking and value checking. 6. Abstracts and simulated devices are easily definable. 7. The high-level IOTs may be considered as input command procedures and entities in a user dialogue language. Use of the IOT model results in ease of programming and efficient execution.
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